Abstract: A computing device includes at least one memory, and at least one processor configured to generate, based on first analysis on a pathological slide image, first biomarker expression information, generate, based on a user input for updating at least some of results of the first analysis, second biomarker expression information about the pathological slide image, and control a display device to output a report including medical information about at least some regions included in the pathological slide image, based on at least one of the first biomarker expression information or the second biomarker expression information.

Abstract: A computing apparatus includes: at least one memory; and at least one processor, wherein the processor generates quantitative information regarding at least one cell included in a region of interest of a pathological slide image by analyzing the pathological slide image, generates qualitative information regarding at least one tissue included in the pathological slide image by analyzing the pathological slide image, and controls a display apparatus to output at least one of the quantitative information and the qualitative information on the pathological slide image according to a manipulation of a user.

Abstract: Provided is a method for analysing a pathology image, which is performed by at least one processor and includes acquiring a pathology image, inputting the acquired pathology image into a machine learning model and acquiring an analysis result for the pathology image from the machine learning model, and outputting the acquired analysis result, in which the machine learning model is a model trained by using a training data set generated based on a first pathology data set associated with a first domain and a second pathology data set associated with a second domain different from the first domain.

Abstract: A computing apparatus includes: at least one memory; and at least one processor, wherein the processor generates quantitative information regarding at least one cell included in a region of interest of a pathological slide image by analyzing the pathological slide image, generates qualitative information regarding at least one tissue included in the pathological slide image by analyzing the pathological slide image, and controls a display apparatus to output at least one of the quantitative information and the qualitative information on the pathological slide image according to a manipulation of a user.

Abstract: A computing device includes at least one memory, and at least one processor configured to generate, based on first analysis on a pathological slide image, first biomarker expression information, generate, based on a user input for updating at least some of results of the first analysis, second biomarker expression information about the pathological slide image, and control a display device to output a report including medical information about at least some regions included in the pathological slide image, based on at least one of the first biomarker expression information or the second biomarker expression information.

Abstract: Provided is a computing device including at least one memory, and at least one processor configured to obtain a first pathological slide image one of a first object and biological information of the first object, generate training data by using at least one first patch included in the first pathological slide image, and the biological information, train a first machine learning model based on the training data, and analyze a second pathological slide image of a second object by using the trained first machine learning model.

Abstract: A computing apparatus includes: at least one memory; and at least one processor, wherein the processor generates quantitative information regarding at least one cell included in a region of interest of a pathological slide image by analyzing the pathological slide image, generates qualitative information regarding at least one tissue included in the pathological slide image by analyzing the pathological slide image, and controls a display apparatus to output at least one of the quantitative information and the qualitative information on the pathological slide image according to a manipulation of a user.

Abstract: A method for operating a medical imaging device includes obtaining lesion information on at least one lesion detected from a medical image, determining a shape and a position of at least one contour corresponding to the at least one lesion based on the obtained lesion information, determining a position of at least one text region that includes a text indicating the lesion information on the at least one lesion in the medical image, and displaying the at least one contour and the text included in the at least one text region on the medical image, based on the determined shape and position of the at least one contour and the determined position of the at least one text region.

Abstract: The present disclosure relates to a medical image analysis method using a processor and a memory which are hardware. The method includes generating predicted second metadata for a medical image by using a prediction model, and determining a processing method of the medical image based on one of first metadata stored corresponding to the medical image and the second metadata.

Abstract: A machine learning method that may reduce an annotation cost and may improve performance of a target model is provided. Some embodiments of the present disclosure may provide a machine learning method performed by a computing device, including: acquiring a training dataset of a first model including a plurality of data samples to which label information is not given; calculating a miss-prediction probability of the first model on the plurality of data samples; configuring a first data sample group by selecting at least one data sample from the plurality of data samples based on the calculated miss-prediction probability; acquiring first label information on the first data sample group; and performing first learning on the first model by using the first data sample group and the first label information.

Abstract: A machine learning method that may reduce an annotation cost and may improve performance of a target model is provided. Some embodiments of the present disclosure may provide a machine learning method performed by a computing device, including: acquiring a training dataset of a first model including a plurality of data samples to which label information is not given; calculating a miss-prediction probability of the first model on the plurality of data samples; configuring a first data sample group by selecting at least one data sample from the plurality of data samples based on the calculated miss-prediction probability; acquiring first label information on the first data sample group; and performing first learning on the first model by using the first data sample group and the first label information.

Abstract: The present disclosure provides a method for training a neural network that extracts a feature of an image by using data related to a difference between image, and an apparatus using the same. A neural network training method performed by a computing device according to an exemplary embodiment of the present disclosure includes: acquiring a reference image photographed with a first setting with respect to an object and a first comparison image photographed with a second setting with respect to the object; acquiring feature data of the reference image from a first neural network trained by using the reference image; acquiring feature data of a first extract image from a second neural network, wherein the second neural network is trained by using the first extract image formed from data related to a difference between the reference image and the first comparison image; and training a third neural network by using the feature data of the reference image and the feature data of the first extracted image.

Abstract: The present invention relates to a classification apparatus for pathologic diagnosis of a medical image and a pathologic diagnosis system using the same. According to the present invention, there is provided a classification apparatus for pathologic diagnosis of a medical image, including: a feature extraction unit configured to extract feature data for an input image using a feature extraction variable; a feature vector transformation unit configured to transform the extracted feature data into a feature vector using a vector transform variable; and a vector classification unit configured to classify the feature vector using a classification variable, and to output the results of the classification of pathologic diagnosis for the input image; wherein the feature extraction unit, the feature vector transformation unit and the vector classification unit are trained based on a first tagged image, a second tagged image, and an image having no tag information.

Abstract: The present invention relates to a classification apparatus for pathologic diagnosis of a medical image and a pathologic diagnosis system using the same. According to the present invention, there is provided a classification apparatus for pathologic diagnosis of a medical image, including: a feature extraction unit configured to extract feature data for an input image using a feature extraction variable; a feature vector transformation unit configured to transform the extracted feature data into a feature vector using a vector transform variable; and a vector classification unit configured to classify the feature vector using a classification variable, and to output the results of the classification of pathologic diagnosis for the input image; wherein the feature extraction unit, the feature vector transformation unit and the vector classification unit are trained based on a first tagged image, a second tagged image, and an image having no tag information.

Abstract: The present invention relates to a cloud-based pathological analysis system and method. The present invention provides a cloud-based pathological analysis system, including: a client device coupled to a microscope, and configured to acquire an image for a tissue sample via the microscope and generate a sample image; and a cloud server coupled to the client device over a network, and configured to receive sample image data from the client device over the network and store the sample image data; wherein the cloud server analyzes the received sample image data, and transmits analysis information to the client device.

Abstract: A visual product searching apparatus includes a product area determining part, a visual word generating part and a product searching part. The product area determining part extracts a product area in an input image. The visual word generating part generates a visual word reflecting human visual cognitive characteristics based on the product area. The product searching part searches a product using the visual word.

Abstract: Provided is a photographing apparatus for investigating a state of an outcrop. The photographing apparatus according to the present invention includes: a photographing unit photographing moving pictures or pictures; and a plurality of laser pointers outputting laser beams toward the outcrops photographed by the photographing unit to form laser points on the outcrops, wherein each laser point is disposed so that the laser beams output therefrom are output in parallel with laser beams output from other laser pointers.

Abstract: Provided is a photographing apparatus for investigating a state of an outcrop. The photographing apparatus according to the present invention includes: a photographing unit photographing moving pictures or pictures; and a plurality of laser pointers outputting laser beams toward the outcrops photographed by the photographing unit to form laser points on the outcrops, wherein each laser point is disposed so that the laser beams output therefrom are output in parallel with laser beams output from other laser pointers.

Abstract: Provided is a boomer that is a type of a seismic source generator for marine seismic survey. In the boomer for marine seismic survey according to the exemplary embodiment of the present invention, a plurality of transducer coupling parts capable of separating and coupling a transducer are disposed on a bottom of a board floating on a surface of water, the transducer coupling parts are disposed along a straight line L forming left and right center of gravity of the board, and a transducer coupling member for mounting a transducer is provided. Further, the support is mounted on the bottom of the board, the transducer coupling part is disposed on the support, and the support is formed to control a distance from a bottom point of the board to the transducer coupling part.